Batch construction.
Nearest neighbors used to construct mini-batches in STML are computed on the student embedding space and update at every epoch.
On the CUB and Cars datasets, each mini-batch consists of 120 images including 24 queries and their 4 nearest neighbors.
Since the SOP dataset has a tiny number of samples per class, we construct a mini-batch with 60 queries and their top-1 neighbors on the dataset.
Also, all images are randomly augmented twice following the multi-view augmentation strategy in [1]}.
